Polymer Diffusion Is Fastest at Intermediate Levels of Cylindrical Confinement

Capillary filling dynamics of polymer melts in a bicontinuous nanoporous scaffold

Polymer infiltrated nanoporous gold is prepared by infiltrating polymer melts into a bicontinuous, nanoporous gold (NPG) scaffold. Polystyrene (PS) films with molecular weights (Mw) from 424 to 1133 kDa are infiltrated into a NPG scaffold (∼120 nm), with a pore radius (Rp) and pore volume fraction of 37.5 nm and 50%, respectively. The confinement ratios (Γ=RgRp) range from 0.47 to 0.77, suggesting that the polymers inside the pores are moderately confined. The time for PS to achieve 80% infiltration (τ80%) is determined using in situ spectroscopic ellipsometry at 150 °C. The kinetics of infiltration scales weaker with Mw, τ80%∝Mw1.30±0.20, than expected from bulk viscosity Mw3.4. Furthermore, the effective viscosity of the PS melt inside NPG, inferred from the Lucas-Washburn model, is reduced by more than one order of magnitude compared to the bulk. Molecular dynamics simulation results are in good agreement with experiments predicting scaling as Mw1.4. The reduced dependence of Mw and the enhanced kinetics of infiltration are attributed to a reduction in chain entanglement density during infiltration and a reduction in polymer-wall friction with increasing polymer molecular weight. Compared to the traditional approach involving adding discrete particles into the polymer matrix, these studies show that nanocomposites with higher loading can be readily prepared, and that kinetics of infiltration are faster due to polymer confinement inside pores. These films have potential as actuators when filled with stimuli-responsive polymers as well as polymer electrolyte and fuel cell membranes.

Disentanglement of Surface and Confinement Effects for Diene Metathesis in Mesoporous Confinement

We study the effects of a planar interface and confinement on a generic catalytically activated ring-closing polymerization reaction near an unstructured catalyst. For this, we employ a coarse-grained polymer model using grand-canonical molecular dynamics simulations with a Monte Carlo reaction scheme. Inspired by recent experiments in the group of M. Buchmeiser that demonstrated an increase in ring-closing selectivity under confinement, we show that both the interface effects, i.e., placing the catalyst near a planar wall, and the confinement effects, i.e., locating the catalyst within a pore, lead to an increase of selectivity. We furthermore demonstrate that curvature effects for cylindrical mesopores (2 nm < d < 12.3 nm) influence the distribution of the chain ends, leading to a further increase in selectivity. This leads us to speculate that specially corrugated surfaces might also help to enhance catalytically activated polymerization processes.

Robust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories

Confinement breaks translational and rotational symmetry in materials and makes all physical properties functions of position. Such spatial variations are key to modulating material properties at the nanoscale, and characterizing them accurately is therefore an intense area of research in the molecular simulations community. This is relatively easy to accomplish for basic mechanical observables. Determining spatial profiles of transport properties, such as diffusivity, is, however, much more challenging, as it requires calculating position-dependent autocorrelations of mechanical observables. In our previous paper (Domingues, T.S.; Coifman, R.; Haji-Akbari, A. J. Phys. Chem. B 2023, 127, 5273 10.1021/acs.jpcb.3c00670), we analytically derive and numerically validate a set of filtered covariance estimators (FCEs) for quantifying spatial variations of the diffusivity tensor from stochastic trajectories. In this work, we adapt these estimators to extract diffusivity profiles from MD trajectories and validate them by applying them to a Lennard-Jones fluid within a slit pore. We find our MD-adapted estimator to exhibit the same qualitative features as its stochastic counterpart, as it accurately estimates the lateral diffusivity across the pore while systematically underestimating the normal diffusivity close to hard boundaries. We introduce a conceptually simple and numerically efficient correction scheme based on simulated annealing and diffusion maps to resolve the latter artifact and obtain normal diffusivity profiles that are consistent with the self-part of the van Hove correlation functions. Our findings demonstrate the potential of this MD-adapted estimator in accurately characterizing spatial variations of diffusivity in confined materials.

Robust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Stochastic Trajectories

Materials under confinement can possess properties that deviate considerably from their bulk counterparts. Indeed, confinement makes all physical properties position-dependent and possibly anisotropic, and characterizing such spatial variations and directionality has been an intense area of focus in experimental and computational studies of confined matter. While this task is fairly straightforward for simple mechanical observables, it is far more daunting for transport properties such as diffusivity that can only be estimated from autocorrelations of mechanical observables. For instance, there are well established methods for estimating diffusivity from experimentally observed or computationally generated trajectories in bulk systems. No rigorous generalizations of such methods, however, exist for confined systems. In this work, we present two filtered covariance estimators for computing anisotropic and position-dependent diffusivity tensors and validate them by applying them to stochastic trajectories generated according to known diffusivity profiles. These estimators can accurately capture spatial variations that span over several orders of magnitude and that assume different functional forms. Our kernel-based approach is also very robust to implementation details such as the localization function and time discretization and performs significantly better than estimators that are solely based on local covariance. Moreover, the kernel function does not have to be localized and can instead belong to a dictionary of orthogonal functions. Therefore, the proposed estimator can be readily used to obtain functional estimates of diffusivity rather than a tabulated collection of pointwise estimates. Nonetheless, the susceptibility of the proposed estimators to time discretization is higher at the immediate vicinity of hard boundaries. We demonstrate this heightened susceptibility to be common among all covariance-based estimators.

Coarse-Grained Modeling of Polymer Cleavage within a Porous Catalytic Support

The chemical upcycling of plastic waste to valuable liquid products requires catalytic cleavage architectures that afford control over the resulting product distributions. Recently, a catalyst was synthesized in which polymer chains are cleaved at the bottoms of pores to yield a narrow distribution of alkane products. An attractive feature of this architecture is the ability to modulate the product distribution by tuning physical parameters like the diameter of the pore. Understanding how such parameters affect product distributions is an important requirement of further synthetic improvements. We demonstrate that the pore diameter controls the products of the cleavage reaction via two distinct mechanisms. Our coarse-grained, particle-based simulations yield insight into the interplay of chain cleavage and pore residence times and show that the pore size can bias which bonds along a chain are cleaved.

Structure and dynamics of a 1,4-polybutadiene melt in an alumina nanopore: A molecular dynamics simulation

We present results of Molecular Dynamics simulations of a chemically realistic model of 1,4-polybutadiene (PBD)confined in a cylindrical alumina nanopore of diameter 10 nm. The simulations are done at three different temperaturesabove the glass transition temperature T g . We investigate the density layering across the nanopore as well as theorientational ordering in the polymer melt, brought about by the confinement, on both the segmental and chain scales.For the chain scale ordering, the magnitude and orientation of the axes of the gyration tensor ellipsoid of single chainsare studied and are found to prefer to align parallel to the pore axis. Even though double bonds near the wall arepreferentially oriented along the pore walls, studying the nematic order parameter indicates that there is no nematicordering at the melt-wall interface. As for the dynamics in the melt, we focus here on the mean-square-displacement ofthe monomers for several layers across the nanopore as well as the movement of the chain center of mass which bothdisplay a slowing down of the dynamics in the layer at the wall. We also show the strong adsorption of the monomersto the pore wall at lower temperatures.

The Interplay of Polymer Bridging and Entanglement in Toughening Polymer-Infiltrated Nanoparticle Films

Polymer-nanoparticle composite films (PNCFs) with high loadings of nanoparticles (NPs) (>50 vol %) have applications in multiple areas, and an understanding of their mechanical properties is essential for their broader use. The high-volume fraction and small size of the NPs lead to physical confinement of the polymers that can drastically change the properties of polymers relative to the bulk. We investigate the fracture behavior of a class of highly loaded PNCFs prepared by polymer infiltration into NP packings. These polymer-infiltrated nanoparticle films (PINFs) have applications as multifunctional coatings and membranes and provide a platform to understand the behavior of polymers that are highly confined. Here, the extent of confinement in PINFs is tuned from 0.1 to 44 and the fracture toughness of PINFs is increased by up to a factor of 12 by varying the molecular weight of the polymers over 3 orders of magnitude and using NPs with diameters ranging from 9 to 100 nm. The results show that brittle, low molecular weight (MW) polymers can significantly toughen NP packings, and this toughening effect becomes less pronounced with increasing NP size. In contrast, high MW polymers capable of forming interchain entanglements are more effective in toughening large NP packings. We propose that confinement has competing effects of polymer bridging increasing toughness and chain disentanglement decreasing toughness. These findings provide insight into the fracture behavior of confined polymers and will guide the development of mechanically robust PINFs as well as other highly loaded PNCFs.

Conformation and dynamics of ring polymers under symmetric thin film confinement

Understanding the structure and dynamics of polymers under confinement has been of widespread interest, and one class of polymers that have received comparatively little attention under confinement is that of ring polymers. The properties of non-concatenated ring polymers can also be important in biological fields because ring polymers have been proven to be a good model to study DNA organization in the cell nucleus. From our previous study, linear polymers in a cylindrically confined polymer melt were found to segregate from each other as a result of the strong correlation hole effect that is enhanced by the confining surfaces. By comparison, our subsequent study of linear polymers in confined thin films at similar levels of confinements found only the onset of segregation. In this study, we use molecular dynamics simulation to investigate the chain conformations and dynamics of ring polymers under planar (1D) confinement as a function of film thickness. Our results show that conformations of ring polymers are similar to the linear polymers under planar confinement, except that ring polymers are less compressed in the direction normal to the walls. While we find that the correlation hole effect is enhanced under confinement, it is not as pronounced as the linear polymers under 2D confinement. Finally, we show that chain dynamics far above Tg are primarily affected by the friction from walls based on the monomeric friction coefficient we get from the Rouse mode analysis.

Modeling of Entangled Polymer Diffusion in Melts and Nanocomposites: A Review

This review concerns modeling studies of the fundamental problem of entangled (reptational) homopolymer diffusion in melts and nanocomposite materials in comparison to experiments. In polymer melts, the developed united atom and multibead spring models predict an exponent of the molecular weight dependence to the polymer diffusion very similar to experiments and the tube reptation model. There are rather unexplored parameters that can influence polymer diffusion such as polymer semiflexibility or polydispersity, leading to a different exponent. Models with soft potentials or slip-springs can estimate accurately the tube model predictions in polymer melts enabling us to reach larger length scales and simulate well entangled polymers. However, in polymer nanocomposites, reptational polymer diffusion is more complicated due to nanoparticle fillers size, loading, geometry and polymer-nanoparticle interactions.